The identification of hazardous road locations is important to the improvement of road safety. However, there is still no consensus on the best method of identifying hazardous road locations. While traditional methods, such as the hot spot methodology, focus on the physical distances separating road crashes only, the hot zone methodology takes network contiguity into consideration and treats contiguous road segments as hazardous road locations. Compared with the hot spot method, hot zone methodology is a relatively new direction and there still remain a number of methodological issues in applying the method to the identification of hazardous road locations. Hence, this study aims to provide a GIS-based study on the identification of crash hot zones as hazardous road locations with both link-attribute and event-based approaches. It first explores the general procedures of the two approaches in identifying traffic crash hot zones, and then investigates the characteristics of the two approaches by conducting a range of sensitivity analysis on defining threshold value and crash intensity with both simulated and empirical data. The results suggest that it is better to use a dissolved road network instead of a raw-link-node road network. The segmentation length and the interval of reference points have great impacts on the identification of hot zones, and they are better defined as 100 meters considering the stabilities of the performance. While employing a numerical definition to identify hot zones is a simple and effort-saving approach, using the Monte Carlo method can avoid selection bias in choosing an appropriate number as the threshold value. If the two approaches are compared, it is observed that the link-attribute approach is more likely to cause false negative problem and the event-based approach is prone to false positive problem around road junctions. No matter which method is used, the link-attribute approach requires less computer time in identifying crash hot zones. When a range of environmental variables have to be taken into consideration, the link-attribute approach is superior to the event-based approach in that it is easier for the link-attribute approach to incorporate environmental variables with statistical models. By investigating the hot zone methodology, this research is expected to enrich the theoretical knowledge of the identification of hazardous road locations and to practically provide policy-makers with more information on identifying road hazards. Further research efforts have to be dedicated to the ranking of hot zones and the investigation of false positive and false negative problems. / published_or_final_version / Geography / Doctoral / Doctor of Philosophy

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A high incidence of road accidents has been recorded in Saudi Arabia in recent years (Traffic Department Statistics 1991). Various factors might have accounted for this high rate of road accidents; the aim of this research, therefore, was to examine what factors contribute to road accidents in the country. In pursuit of this aim, a review of relevant literature on factors related with road accidents in many countries of the world was undertaken. Through this review, a list of road, vehicle and driver-related variables was selected for investigation in this study. The target population for the study was 4,100 drivers in Eastern Saudi Arabia who had been involved in road accidents in the period. Out of this population, a sample of 600 drivers was selected. The instrument used to collect data for the study was a questionnaire which requested demographic information on factors which had caused them to have an accident, and questions analysing habitual driving behaviour. Drivers were also tested on their knowledge of road signs. Returns were received from 484 drivers, 81% of the study sample. Two statistical techniques, chi square and correlation coefficient Spearman Brown formula, were utilised to test the relationship between the independent variables and the dependent variable - the number of road accidents. The findings of the study show that certain variables were significantly associated with road accidents in Saudi Arabia. Among the significant variables were the age of the driver, education level, profession, violation record, vehicle ownership, joy-riding, poor eye sight, sun haze, sand storm, long hours driving, non-observance of speed limit, emerging and exiting from roads without signals, presence of stray animals, non-marking of the road, non-familiarity with the road, lack of regular checking of vehicles, lack of regular servicing of vehicles and driving under medication. The variables that were not significant include marital status, non-possession of a licence, mechanical fault, reversing, non-alertness to others' errors, use of high beam lights while driving, non-lighting of the roads, passengers' behaviour, ear disorder. Conclusions were drawn as to deficiencies in driver training in Saudi Arabia and inadequacies of supervision by the law enforcement agents. It is recommended that policy makers should make intensive efforts in organising training programmes and seminars for drivers and curriculum of driving schools should be expanded. Measures for improving enforcement of traffic regulations are made, and it is suggested that an Islamic insurance policy for vehicles should be introduced in the country. Finally, suggestions are made for further research.

Thesis (MEng)--University of South Australia, 1999

Thesis (MEng)--University of South Australia, 1999

Thesis (MEng)--University of South Australia, 1999

Thesis (Ph. D.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (p. 233-269). Also available via the World Wide Web.

Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (leaves [120]-128).

Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (leaves [161]-165).

Thesis (doctoral)--Universität Marburg, 1913. / Includes bibliographical references (p. [5-6]).